Collaborative Computation Offloading for Multiaccess Edge Computing Over Fiber–Wireless Networks

By Hongzhi Guo, Jiajia Liu. IEEE Transactions on Vehicular Technology, 2018

315 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/7e36a0fa4cdc0105bd4a0f607d17395ed3e7adb7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Jiajia Liu
2. Nei Kato
3. Zubair Muhammad Fadlullah
4. Shengli Xie
5. Yanning Zhang
6. Hongzhi Guo
7. Weisong Shi
8. Fengxiao Tang

In Computer Networks and Communications

1. Jiajia Liu
2. Nei Kato
3. Zubair Muhammad Fadlullah
4. Mugen Peng
5. Ju Ren
6. Deyu Zhang
7. Tao Li
8. Hongzhi Guo

In Electrical and Electronic Engineering

1. Nei Kato
2. Jiajia Liu
3. Mugen Peng
4. Zubair Muhammad Fadlullah
5. Hongzhi Guo
6. Yongpeng Shi
7. Weisong Shi
8. Jiadai Wang

Citations in the corpus

• Task Offloading in Vehicular Edge Computing Networks: A Load-Balancing Solution (2020, background): “[20] studied the task offloading problem”
• Edge-Computing-Enabled Smart Cities: A Comprehensive Survey (2019, unknown): “A user offloads either all components of an application (binary offloading) [103]–[105] or some components of an application to the edge server (partial”
• Resource Scheduling in Edge Computing: A Survey (2021, background): “Guo and Liu in [52] introduced the concept of a hybrid fiber-wireless (FiWi) network, in which the multiaccess edge computing and the centralized cloud computing cooperated to provide better offloading performance and good scalability as computation tasks increase.”
• A Survey on End-Edge-Cloud Orchestrated Network Computing Paradigms (2019, background): “Reference [65] investigates the computation offloading in a three-level hierarchy, in which the MDs are connected to edge servers through wireless links, and the edge servers connect with the cloud server by optical fibers.”
• Deep Reinforcement Learning for Offloading and Resource Allocation in Vehicle Edge Computing and Networks (2019, background): “Some novel MEC-based vehicular networks are proposed in [25], [26], in which the computation”
• Networking and Communications in Autonomous Driving: A Survey (2019, background): “Besides, autonomous vehicles need to make fast decisions on their control, perform path planning, process the perceptual data in real time and take driving action accordingly, while edge computing, as one of the 5G technologies and the extension of cloud computing to edge networks [195], can provide”
• Toward Edge Intelligence: Multiaccess Edge Computing for 5G and Internet of Things (2020, background): “2) Offloading to Collaborative/Hybrid MCC and MEC: Guo and Liu [77] studied the problem of cloud-MEC”
• A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art (2019, unknown): “In [41], [310], [311], a general architecture of hybrid fiber-wireless (FiWi) networks for the coexistence of centralized cloud and distributed MEC servers was proposed.”
• Space-Air-Ground Integrated Network: A Survey (2018, background): “and game theory [186] and auction theory [187] should be introduced.”